A virtual “talking head,” which can express a full range of human emotions and could be used as a digital personal assistant, has been developed by researchers at Toshiba’s Cambridge Research Lab and the University of Cambridge’s Department of Engineering.

Known as Zoe, the talking head is based on the face of actress Zoe Lister, who plays Zoe Carpenter in the Channel 4 series Hollyoaks. Zoe can display emotions such as happiness, anger, and fear, and changes its voice to suit the feeling that the user wants it to simulate.

Users can type in a message, specifying the requisite emotion or combination of emotions, and the face will recite the text. According to its designers, Zoe is the most expressive controllable avatar ever created, replicating human emotions with “unprecedented realism”.

Israeli startup Oryx Vision has raised a $50 million Series B round led by Third Point Ventures and WRV to help continue to develop and commercialize its innovative LiDAR tech, which is designed to be as simple as a digital camera with greater reliability and sensitivity than existing LiDAR, while also achieving a low cost.

Oryx’s LiDAR has no moving parts, and uses antennas in place of photodetectors to retrieve both range and velocity information for the points of light in its high-resolution scans of its surroundings. Oryx says its unique method means that the system is “a million times more sensitive” than existing LiDAR systems, and is also able to deal better with interference from sunlight, and from other LiDARs in operation on the road.

SpaceX's drone landing ships have already proven that uncrewed vessels can handle some of the most dangerous jobs at sea. Now, two Norwegian companies are poised to put robo-boats into one of the most dull: hauling cargo down the fjord.

Two Norwegian companies are teaming together to construct a short-range, all-electric coastal container ship that will eventually operate autonomously—eliminating up to 40,000 diesel truck trips per year. The ship, the Yara Birkeland, will begin operations in 2018 with a crew, but it's expected to operate largely autonomously (and crewless) by 2020 (regulatory clearance permitting, of course).

The UK government has announced plans to introduce drone registration and safety awareness courses for owners of the small unmanned aircraft. It will affect anyone who owns a drone which weighs more than 250 grams (8oz). Drone maker DJI said it was in favour of the measures. There is no time frame or firm plans as to how the new rules will be enforced and the Department of Transport admitted that "the nuts and bolts still have to be ironed out".

Partially autonomous and intelligent systems have been used in military technology since at least the Second World War, but advances in machine learning and Artificial Intelligence (AI) represent a turning point in the use of automation in warfare. Though the United States military and intelligence communities are planning for expanded use of AI across their portfolios, many of the most transformative applications of AI have not yet been addressed.

In this piece, we propose three goals for developing future policy on AI and national security: preserving U.S. technological leadership, supporting peaceful and commercial use, and mitigating catastrophic risk. By looking at four prior cases of transformative military technology—nuclear, aerospace, cyber, and biotech—we develop lessons learned and recommendations for national security policy toward AI.

Lyft has been coming after Uber’s crown at full force, and it’s showing no signs of slowing. The ridesharing company has continued to charge through the door that’s been left wide open by Uber, and in its latest move, has begun developing self-driving technology of its own. On Friday, the firm announced that it was venturing into autonomous vehicles, and has opened a new self-driving-research center in Palo Alto, California. In the next few weeks, Lyft expects to hire a number of new engineering and technical folks to staff this new facility, and hopefully, overtake Uber as the leader in the future of transportation.

During nearly every discussion about organizational change, someone makes the obvious assertion that “change is hard.” On the surface, this is true: change requires effort. But the problem with this attitude, which permeates all levels of our organizations, is that it equates “hard” with “failure,” and, by doing so, it hobbles our change initiatives, which have higher success rates than we lead ourselves to believe.

Our biases toward failure is wired into our brains. In a recently published series of studies, University of Chicago researchers Ed O’Brien and Nadav Klein found that we assume that failure is a more likely outcome than success, and, as a result, we wrongly treat successful outcomes as flukes and bad results as irrefutable proof that change is difficult.

Blockchain is a distributed database which is cryptographically protected against malicious modifications. While promising for a wide range of applications, current blockchain platforms rely on digital signatures, which are vulnerable to attacks by means of quantum computers. The same, albeit to a lesser extent, applies to cryptographic hash functions that are used in preparing new blocks, so parties with access to quantum computation would have unfair advantage in procuring mining rewards. Here we propose a possible solution to the quantum-era blockchain challenge and report an experimental realization of a quantum-safe blockchain platform that utilizes quantum key distribution across an urban fiber network for information-theoretically secure authentication. These results address important questions about realizability and scalability of quantum-safe blockchains for commercial and governmental applications.

It is a battle for domination over the individual nodes (people) and their social graphs.

By instrumentalizing and conquering individual nodes, they are able to interfere and influence their social graph (see: Human Data Banks and Algorithmic Labor, SHARE Labs 20161) consisted of their social circles, hundreds of friends, colleagues and relatives. This doctrine is about conquering information streams of others through proxies. Social network ecosystems are fertile ground for different form of disinformation or smear campaigns against opponents, or just a cheerleading activities, depending on the style of the political warfare. In such environment, political propaganda (spreading of ideas, information, or rumor for the purpose of helping or injuring an institution, a cause, or a person 2), can be executed through individual nodes that are anonymous or without visible, direct connection of their real-life identities to a political party.

Artificial intelligence is now powering a growing number of computing functions, and today the developer community today is getting another AI boost, courtesy of Yandex. Today, the Russian search giant — which, like its US counterpart Google, has extended into a myriad of other business lines, from mobile to maps and more — announced the launch of CatBoost, an open source machine learning library based on gradient boosting — the branch of ML that is specifically designed to help “teach” systems when you have a very sparse amount of data, and especially when the data may not all be sensorial (such as audio, text or imagery), but includes transactional or historical data, too.

IN 1899, THE world’s most powerful nations signed a treaty at The Hague that banned military use of aircraft, fearing the emerging technology’s destructive power. Five years later the moratorium was allowed to expire, and before long aircraft were helping to enable the slaughter of World War I. “Some technologies are so powerful as to be irresistible,” says Greg Allen, a fellow at the Center for New American Security, a non-partisan Washington DC think tank. “Militaries around the world have essentially come to the same conclusion with respect to artificial intelligence.” Allen is coauthor of a 132-page new report on the effect of artificial intelligence on national security. One of its conclusions is that the impact of technologies such as autonomous robots on war and international relations could rival that of nuclear weapons. The report was produced by Harvard’s Belfer Center for Science and International Affairs, at the request of IARPA, the research agency of the Office of the Director of National Intelligence. It lays out why technologies like drones with bird-like agility, robot hackers, and software that generates photo-real fake video are on track to make the American military and its rivals much more powerful.

XL Catlin today announced the launch of its Cyber and Data Protection Insurance policy in Asia Pacific. With cyber risk ranking in the top 10 in today’s emerging risks, the new policy is designed to protect businesses from the increasing exposures they face from a malicious network compromise and data breach.

The insurance solution covers business interruption arising from a network compromise, associated extortion demands and first party incident response costs such as notification of the compromise of the network, forensic investigations and public relations support. Importantly, the policy covers third-party liability costs that organisations face as a result of a data breach, including any regulatory investigation or contractual liability associated with the Payment Card Industry Data Security Standard. Additionally, it offers broad coverage for liability associated with media exposures such as copyright infringement, trademark infringement, invasion of privacy and false advertising, in both offline and online content as well as social media.

Like its namesake, Baidu’s Project Apollo aims to redefine the possibilities for human travel. But instead of landing men on the moon like NASA’s version of the program, vehicles in this initiative must learn to drive themselves. In April, Baidu announced Project Apollo — an open source platform for self-driving that includes hardware, software and …

Our brains have evolved to recognize and remember faces. As infants, one of the first things we learn is to look at the faces of those around us, respond to eye contact and mimic facial expressions. As adults, this translates to an ability to recognize human faces better and faster than other visual stimuli. We’re able to instantly identify a friend’s face among dozens in a crowded restaurant or on a city street. And we can glean whether they’re excited or angry, happy or sad, from just a glance.

This is the second story in our investigation trilogy titled Facebook Algorithmic Factory, created with the intention to map and visualise a complex and invisible exploitation process hidden behind a black box of the World’s largest social network.

The following map is one of the final results of our investigation, but it can also be used as a guide through our stories, and practically help the reader to remain in the right direction and not to get lost in the complex maze of the Facebook Algorithmic Factory.

We are creatures of habits, and we tend to create repetitions and patterns in our everyday behaviour. We tend to go to bed and wake up at similar times, to create our morning routines and create rituals of our social interactions. Since many segments of our lives are mediated by technology, those patterns are replicated and visible through the different digital footprints. When patterns are recognised, anomaly detection is born. As stated by Pasquinelli8, the two epistemic poles of pattern and anomaly are the two sides of the same coin of algorithmic governance. An unexpected anomaly can be detected only against the ground of a pattern regularity.

Both pattern recognition and anomaly detection are used as methods for understanding the vast quantity of data, our digital footprints that are being collected by many actors, from government agencies around the globe, internet companies and service providers or data dealers.

Something recognised as an anomaly in the eye of the algorithm can put you on the watchlist of a government agency or some behavioral pattern can label you as a target for an online advertisement. In the case of Mr. J simple bar charts and heatmap based on the number of browsing actions in time can reveal few patterns of behaviour.

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